Measuring Technological Innovation Over the Long Run

79 Pages Posted: 19 Nov 2018

See all articles by Bryan T. Kelly

Bryan T. Kelly

Yale SOM; AQR Capital Management, LLC; National Bureau of Economic Research (NBER)

Dimitris Papanikolaou

Northwestern University - Kellogg School of Management - Department of Finance; National Bureau of Economic Research (NBER)

Amit Seru

Stanford University

Matt Taddy

University of Chicago

Multiple version iconThere are 2 versions of this paper

Date Written: November 2018

Abstract

We use textual analysis of high-dimensional data from patent documents to create new indicators of technological innovation. We identify significant patents based on textual similarity of a given patent to previous and subsequent work: these patents are distinct from previous work but are related to subsequent innovations. Our measure of patent significance is predictive of future citations and correlates strongly with measures of market value. We identify breakthrough innovations as the most significant patents – those in the right tail of our measure – to construct indices of technological change at the aggregate, sectoral, and firm level. Our technology indices span two centuries (1840-2010) and cover innovation by private and public firms, as well as non-profit organizations and the US government. These indices capture the evolution of technological waves over a long time span and are strong predictors of productivity at the aggregate, sectoral, and firm level.

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Suggested Citation

Kelly, Bryan T. and Papanikolaou, Dimitris and Seru, Amit and Taddy, Matt, Measuring Technological Innovation Over the Long Run (November 2018). NBER Working Paper No. w25266. Available at SSRN: https://ssrn.com/abstract=3286887

Bryan T. Kelly (Contact Author)

Yale SOM ( email )

135 Prospect Street
P.O. Box 208200
New Haven, CT 06520-8200
United States

AQR Capital Management, LLC ( email )

Greenwich, CT
United States

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Dimitris Papanikolaou

Northwestern University - Kellogg School of Management - Department of Finance ( email )

Evanston, IL 60208
United States

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Amit Seru

Stanford University ( email )

Stanford, CA 94305
United States

Matt Taddy

University of Chicago ( email )

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